Interactome-Wide Prediction of Protein-Protein Binding Sites Reveals Effects of Protein Sequence Variation in Arabidopsis thaliana

The specificity of protein-protein interactions is encoded in those parts of the sequence that compose the binding interface. Therefore, understanding how changes in protein sequence influence interaction specificity, and possibly the phenotype, requires knowing the location of binding sites in those sequences. However, large-scale detection of protein interfaces remains a challenge. Here, we present a sequence- and interactome-based approach to mine interaction motifs from the recently published Arabidopsis thaliana interactome. The resultant proteome-wide predictions are available via www.ab.wur.nl/sliderbio and set the stage for further investigations of protein-protein binding sites. To assess our method, we first show that, by using a priori information calculated from protein sequences, such as evolutionary conservation and residue surface accessibility, we improve the performance of interface prediction compared to using only interactome data. Next, we present evidence for the functional importance of the predicted sites, which are under stronger selective pressure than the rest of protein sequence. We also observe a tendency for compensatory mutations in the binding sites of interacting proteins. Subsequently, we interrogated the interactome data to formulate testable hypotheses for the molecular mechanisms underlying effects of protein sequence mutations. Examples include proteins relevant for various developmental processes. Finally, we observed, by analysing pairs of paralogs, a correlation between functional divergence and sequence divergence in interaction sites. This analysis suggests that large-scale prediction of binding sites can cast light on evolutionary processes that shape protein-protein interaction networks.

蛋白质-蛋白质相互作用的特异性编码于构成结合界面（binding interface）的序列区域内。因此，要明晰蛋白质序列的变化如何影响相互作用特异性，乃至可能波及表型，就必须明确这些序列中结合位点（binding site）的位置。然而，大规模检测蛋白质界面仍是一项颇具挑战性的课题。本研究提出一种基于序列与相互作用组（interactome）的方法，从最新发表的拟南芥（Arabidopsis thaliana）相互作用组中挖掘相互作用基序。由此得到的全蛋白质组预测结果可通过www.ab.wur.nl/sliderbio获取，为后续开展蛋白质-蛋白质结合位点的相关研究奠定了基础。为评估本方法的性能，我们首先证实：相较于仅使用相互作用组数据，通过利用从蛋白质序列计算得到的先验信息（如进化保守性与残基表面可及性），可显著提升界面预测的性能。随后，我们提供证据表明，预测得到的结合位点相较于蛋白质序列的其余区域承受更强的选择压力，这印证了其功能重要性。我们还观察到，相互作用蛋白质的结合位点存在补偿性突变的倾向。继而，我们对相互作用组数据进行深入挖掘，为蛋白质序列突变效应背后的分子机制构建可验证的假说，相关示例涵盖参与多种发育过程的蛋白质。最后，通过分析旁系同源基因（paralogs）对，我们观察到相互作用位点的功能分化与序列分化之间存在显著相关性。本分析表明，大规模预测结合位点可助力阐明塑造蛋白质-蛋白质相互作用网络的进化过程。